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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Precise and fast microdroplet size distribution measurement using deep learning
Shuyuan Zhang, Liang Xiao, Xinye Huang, et al.
Chemical Engineering Science (2021) Vol. 247, pp. 116926-116926
Closed Access | Times Cited: 31

Showing 1-25 of 31 citing articles:

Machine Learning Approaches in Polymer Science: Progress and Fundamental for a New Paradigm
Chunhui Xie, Haoke Qiu, Lu Liu, et al.
SmartMat (2025) Vol. 6, Iss. 1
Open Access
3D printing and artificial intelligence tools for droplet microfluidics: Advances in the generation and analysis of emulsions
Sibilla Orsini, Marco Lauricella, Andrea Montessori, et al.
Applied Physics Reviews (2025) Vol. 12, Iss. 1
Closed Access
Functions and applications of artificial intelligence in droplet microfluidics
Huan Liu, Lang Nan, Feng Chen, et al.
Lab on a Chip (2023) Vol. 23, Iss. 11, pp. 2497-2513
Closed Access | Times Cited: 19
Deep learning with microfluidics for on-chip droplet generation, control, and analysis
Hao Sun, Wantao Xie, Jin Mo, et al.
Frontiers in Bioengineering and Biotechnology (2023) Vol. 11
Open Access | Times Cited: 18
Accelerating intelligent microfluidic image processing with transfer deep learning: A microchannel droplet/bubble breakup case study
Shuyuan Zhang, Haoran Li, Kai Wang, et al.
Separation and Purification Technology (2023) Vol. 315, pp. 123703-123703
Closed Access | Times Cited: 14
Deep learning-augmented T-junction droplet generation
Abdollah Ahmadpour, Mostafa Shojaeian, Savaş Taşoğlu
iScience (2024) Vol. 27, Iss. 4, pp. 109326-109326
Open Access | Times Cited: 3
Deep learning-based on-line image analysis for continuous industrial crystallization processes
Shiliang Zong, Guangzheng Zhou, Meng Li, et al.
Particuology (2022) Vol. 74, pp. 173-183
Closed Access | Times Cited: 16
Two deep learning methods in comparison to characterize droplet sizes in emulsification flow processes
Inga Burke, Thajeevan Dhayaparan, Ahmed S. A. Youssef, et al.
Journal of Flow Chemistry (2024)
Open Access | Times Cited: 2
Microfluidic droplet detection via region-based and single-pass convolutional neural networks with comparison to conventional image analysis methodologies
Gregory Rutkowski, Ilgar Azizov, Evan Unmann, et al.
Machine Learning with Applications (2021) Vol. 7, pp. 100222-100222
Open Access | Times Cited: 20
A verified open-access AI-based chemical microparticle image database for in-situ particle visualization and quantification in multi-phase flow
Jian Liu, Qingyang Zhang, Mingyang Chen, et al.
Chemical Engineering Journal (2022) Vol. 451, pp. 138940-138940
Closed Access | Times Cited: 13
A dynamic-inner convolutional autoencoder for process monitoring
Shuyuan Zhang, Tong Qiu
Computers & Chemical Engineering (2021) Vol. 158, pp. 107654-107654
Closed Access | Times Cited: 18
Synthetic Image Analysis for Accurate Agglomerate Characterization and Control in Liquid–Liquid Phase Separation Systems
Xiaomeng Zhou, Shutian Xuanyuan, Yang Ye, et al.
Crystal Growth & Design (2024) Vol. 24, Iss. 11, pp. 4572-4581
Closed Access | Times Cited: 1
Numerical simulations to determine the size of microdroplets without visualization by measuring pressure fluctuations
B. Khan, Sunil Kumar Thamida, Anil B. Vir
Deleted Journal (2024) Vol. 1, Iss. 3
Open Access | Times Cited: 1
A deep learning-powered intelligent microdroplet analysis workflow for in-situ monitoring and evaluation of a dynamic emulsion
Jian Liu, Muyang Li, Jingwei Cai, et al.
Chemical Engineering Journal (2024), pp. 155927-155927
Closed Access | Times Cited: 1
Revealing the role of polymer in the robust preparation of the 2,4-dichlorophenoxyacetic acid metastable crystal form by AI-based image analysis
Lan Fang, Jian Liu, Dandan Han, et al.
Powder Technology (2022) Vol. 413, pp. 118077-118077
Closed Access | Times Cited: 7
The Effect of Junction Gutters for the Upscaling of Droplet Generation in a Microfluidic T-Junction
H. Viswanathan
Microgravity Science and Technology (2022) Vol. 34, Iss. 3
Open Access | Times Cited: 6
An Integrated Method of Bayesian Optimization and D-Optimal Design for Chemical Experiment Optimization
Xinye Huang, Shuyuan Zhang, Haoran Li, et al.
Processes (2022) Vol. 11, Iss. 1, pp. 87-87
Open Access | Times Cited: 5
Insight into Microdispersion Flows with a Novel Video Deep Learning Method
Shuyuan Zhang, Qin Kang, Xinye Huang, et al.
Advanced Intelligent Systems (2022) Vol. 4, Iss. 11
Open Access | Times Cited: 5
Advancing Liquid Level Recognition: A Combined Deep Learning and Pixel Manipulation Approach
Borui Yang, Jinsong Zhao
Computer-aided chemical engineering/Computer aided chemical engineering (2024), pp. 1819-1824
Closed Access
A precise and fast droplet parameter inversion algorithm for rainbow scattering detection
Tianchi Li, Can Li, Ning Li
IEEE Sensors Journal (2024) Vol. 24, Iss. 19, pp. 30608-30618
Closed Access
Non-Destructive Measurement of Rice Spikelet Size Based on Panicle Structure Using Deep Learning Method
Ruoling Deng, Weisen Liu, Haitao Liu, et al.
Agronomy (2024) Vol. 14, Iss. 10, pp. 2398-2398
Open Access
On-line image analysis for evaporative crystallization of xylose
Qihang Zhu, Guangzheng Zhou, Gary G. Hou, et al.
Powder Technology (2024), pp. 120446-120446
Closed Access
Direct Optical Measurement for Particle Dynamics in Multiphase Reactors: Hardware Composition, Image Processing and Uncertainties
Xinyi Chen, Qi Kang, Li Qin, et al.
Industrial & Engineering Chemistry Research (2024)
Closed Access
Deep Learning-Based Classification and Quantification of Emulsion Droplets: A YOLOv7 Approach
João Mendes, Adriano S. Silva, Fernanda F. Roman, et al.
Communications in computer and information science (2024), pp. 148-163
Closed Access
Non-destructive measurement of rice grain size based on panicle structure using deep learning method
Ruoling Deng, Long Qi, Jing Zhang, et al.
Research Square (Research Square) (2024)
Open Access
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